Direct-acting antiviral treatment uptake and sustained virological response outcomes are not affected by alcohol use: A CANUHC analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Alcohol use and hepatitis C virus (HCV) are two leading causes of liver disease. Alcohol use is prevalent among the HCV-infected population and accelerates the progression of HCV-related liver disease. Despite barriers to care faced by HCV-infected patients who use alcohol, few studies have analyzed uptake of direct-acting antiviral (DAA) treatment. OBJECTIVE: We compared rates of treatment uptake and sustained virological response (SVR) between patients with and without alcohol use. METHODS: Prospective data were obtained from the Canadian Network Undertaking against Hepatitis C (CANUHC) cohort. Consenting patients assessed for DAA treatment between January 2016 and December 2019 were included. Demographic and clinical characteristics were compared between patients with and without alcohol use by means of t-tests, χ 2 tests, and Fisher’s Exact Tests. Univariate and multivariate analyses were used to determine predictors of SVR and treatment initiation. RESULTS: Current alcohol use was reported for 217 of 725 (30%) patients. The proportion of patients initiating DAA treatment did not vary by alcohol use status (82% versus 83%; p = 0.99). SVR rate was similar between patients with alcohol use and patients without alcohol use (92% versus 94%; p = 0.45). Univariate and multivariate analysis found no association between alcohol use and SVR or treatment initiation. CONCLUSION: Patients engaged in HCV treatment have highly favourable treatment uptake and outcomes regardless of alcohol use. Public health interventions should be directed toward facilitating access to care for all patients irrespective of alcohol use. Research into high-level alcohol use and DAA outcomes is needed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it